Statistical estimation of spatial wave extremes for tropical cyclones from small data samples: validation of the STM-E approach using long-term synthetic cyclone data for the Caribbean Sea

Wada, Ryota; Rohmer, Jeremy; Krien, Yann; Jonathan, Philip

doi:https://doi.org/10.5194/nhess-22-431-2022

Articles | Volume 22, issue 2

https://doi.org/10.5194/nhess-22-431-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Coastal hazards and hydro-meteorological extremes

https://doi.org/10.5194/nhess-22-431-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 2

Research article

|

14 Feb 2022

Research article |

| 14 Feb 2022

Statistical estimation of spatial wave extremes for tropical cyclones from small data samples: validation of the STM-E approach using long-term synthetic cyclone data for the Caribbean Sea

Ryota Wada, Jeremy Rohmer, Yann Krien, and Philip Jonathan

Data sets

Synthetic tropical cyclone data for the Caribbean Sea Y. Krien, R. Wada, J. Rohmer, and P. Jonathan https://doi.org/10.5281/zenodo.4627903

Model code and software

STM-E (space-time maxima and exposure) spatial extremes model for tropical cyclones R. Wada, J. Rohmer, Y. Krien, and P. Jonathan https://github.com/ygraigarw/STM-E

Short summary

Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near Guadeloupe is difficult because cyclones rarely pass near the location of interest. STM-E (space-time maxima and exposure) model utilizes wave data during cyclones on a spatial neighbourhood. Long-duration wave data generated from a database of synthetic tropical cyclones are used to evaluate the performance of STM-E. Results indicate STM-E provides estimates with small bias and realistic uncertainty.